This week has been a deep dive into the world of data collection methods, with a particular focus on triangulation. It all started with my action research project aimed at improving pass rates in online higher education courses using game-based learning strategies. I realized early on that if I wanted my interventions to truly make a difference, robust data collection would be the key to figuring out what works and what doesn’t.
Triangulation, I’ve learned, is an incredibly powerful approach. The idea of using multiple data collection methods to cross-validate findings just makes sense. It’s like getting different perspectives on the same issue. By mixing qualitative and quantitative data—things like student performance metrics, engagement levels, feedback, and assessments—I’m hoping to get a fuller picture of how gamification is affecting learning outcomes and overall course performance. It’s kind of like piecing together a puzzle where each method adds a bit more clarity to the overall picture.
Triangulation in research is like navigating with a map in unfamiliar territory. Just as a traveler might use multiple landmarks to pinpoint their exact location, triangulation uses different data sources to find the most accurate understanding of a research question. Each data point—like each landmark—adds a layer of confidence, guiding us through the complexities and helping us arrive at the most reliable conclusions.
I’m considering starting with surveys and questionnaires to gather students’ thoughts on the game-based elements I’ve introduced. By using open-ended questions and Likert scales, I hope to uncover trends in how students perceive gamification, identify areas where they feel it could be improved, and gain an understanding of their attitudes toward these strategies.
I’m also thinking about incorporating feedback mechanisms into the games to measure how students interact with the game elements within the online courses. By observing their engagement, struggles, and moments of excitement in this way, I aim to gain a deeper understanding of the challenges they face and the successes they experience. This could help me identify patterns and trends that might not be apparent through surveys alone, allowing for more informed adjustments to the instructional design.
Another approach I’m considering is diving into learning analytics by utilizing LMS tools that track student performance, progress, and interaction with the course content. By analyzing this quantitative data, I hope to pinpoint where students are excelling and where they encounter obstacles. This data could serve as a roadmap, guiding me toward areas that need improvement and helping to refine my approach.
As I reflect on all of this, I’m convinced that using diverse data collection methods, especially triangulation, can drive real, positive change. It’s not just about numbers or observations—it’s about bringing everything together to create a more complete picture. And in doing so, I’m hopeful that I can craft learning experiences that not only engage students but also empower them to succeed. This journey into data collection has shown me that when we let data guide our actions, we can truly make a difference in education.
Comments